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We investigate methods and tools for analysing translations between programming languages with respect to observational semantics. The behaviour of programs is observed in terms of may- and mustconvergence in arbitrary contexts, and adequacy of translations, i.e., the reflection of program equivalence, is taken to be the fundamental correctness condition. For compositional translations we propose a notion of convergence equivalence as a means for proving adequacy. This technique avoids explicit reasoning about contexts, and is able to deal with the subtle role of typing in implementations of language extensions.
The paper proposes a variation of simulation for checking and proving contextual equivalence in a non-deterministic call-by-need lambda-calculus with constructors, case, seq, and a letrec with cyclic dependencies. It also proposes a novel method to prove its correctness. The calculus’ semantics is based on a small-step rewrite semantics and on may-convergence. The cyclic nature of letrec bindings, as well as nondeterminism, makes known approaches to prove that simulation implies contextual equivalence, such as Howe’s proof technique, inapplicable in this setting. The basic technique for the simulation as well as the correctness proof is called pre-evaluation, which computes a set of answers for every closed expression. If simulation succeeds in finite computation depth, then it is guaranteed to show contextual preorder of expressions.
This paper proves several generic variants of context lemmas and thus contributes to improving the tools for observational semantics of deterministic and non-deterministic higher-order calculi that use a small-step reduction semantics. The generic (sharing) context lemmas are provided for may- as well as two variants of must-convergence, which hold in a broad class of extended process- and extended lambda calculi, if the calculi satisfy certain natural conditions. As a guide-line, the proofs of the context lemmas are valid in call-by-need calculi, in callby-value calculi if substitution is restricted to variable-by-variable and in process calculi like variants of the π-calculus. For calculi employing beta-reduction using a call-by-name or call-by-value strategy or similar reduction rules, some iu-variants of ciu-theorems are obtained from our context lemmas. Our results reestablish several context lemmas already proved in the literature, and also provide some new context lemmas as well as some new variants of the ciu-theorem. To make the results widely applicable, we use a higher-order abstract syntax that allows untyped calculi as well as certain simple typing schemes. The approach may lead to a unifying view of higher-order calculi, reduction, and observational equality.
This paper proves several generic variants of context lemmas and thus contributes to improving the tools to develop observational semantics that is based on a reduction semantics for a language. The context lemmas are provided for may- as well as two variants of mustconvergence and a wide class of extended lambda calculi, which satisfy certain abstract conditions. The calculi must have a form of node sharing, e.g. plain beta reduction is not permitted. There are two variants, weakly sharing calculi, where the beta-reduction is only permitted for arguments that are variables, and strongly sharing calculi, which roughly correspond to call-by-need calculi, where beta-reduction is completely replaced by a sharing variant. The calculi must obey three abstract assumptions, which are in general easily recognizable given the syntax and the reduction rules. The generic context lemmas have as instances several context lemmas already proved in the literature for specific lambda calculi with sharing. The scope of the generic context lemmas comprises not only call-by-need calculi, but also call-by-value calculi with a form of built-in sharing. Investigations in other, new variants of extended lambda-calculi with sharing, where the language or the reduction rules and/or strategy varies, will be simplified by our result, since specific context lemmas are immediately derivable from the generic context lemma, provided our abstract conditions are met.
We present a higher-order call-by-need lambda calculus enriched with constructors, case-expressions, recursive letrec-expressions, a seq-operator for sequential evaluation and a non-deterministic operator amb that is locally bottom-avoiding. We use a small-step operational semantics in form of a single-step rewriting system that defines a (nondeterministic) normal order reduction. This strategy can be made fair by adding resources for bookkeeping. As equational theory we use contextual equivalence, i.e. terms are equal if plugged into any program context their termination behaviour is the same, where we use a combination of may- as well as must-convergence, which is appropriate for non-deterministic computations. We show that we can drop the fairness condition for equational reasoning, since the valid equations w.r.t. normal order reduction are the same as for fair normal order reduction. We evolve different proof tools for proving correctness of program transformations, in particular, a context lemma for may- as well as mustconvergence is proved, which restricts the number of contexts that need to be examined for proving contextual equivalence. In combination with so-called complete sets of commuting and forking diagrams we show that all the deterministic reduction rules and also some additional transformations preserve contextual equivalence.We also prove a standardisation theorem for fair normal order reduction. The structure of the ordering <=c a is also analysed: Ω is not a least element, and <=c already implies contextual equivalence w.r.t. may-convergence.
We present a higher-order call-by-need lambda calculus enriched with constructors, case-expressions, recursive letrec-expressions, a seq-operator for sequential evaluation and a non-deterministic operator amb that is locally bottom-avoiding. We use a small-step operational semantics in form of a single-step rewriting system that defines a (nondeterministic) normal order reduction. This strategy can be made fair by adding resources for bookkeeping. As equational theory we use contextual equivalence, i.e. terms are equal if plugged into any program context their termination behaviour is the same, where we use a combination of may- as well as must-convergence, which is appropriate for non-deterministic computations. We show that we can drop the fairness condition for equational reasoning, since the valid equations w.r.t. normal order reduction are the same as for fair normal order reduction. We evolve different proof tools for proving correctness of program transformations, in particular, a context lemma for may- as well as mustconvergence is proved, which restricts the number of contexts that need to be examined for proving contextual equivalence. In combination with so-called complete sets of commuting and forking diagrams we show that all the deterministic reduction rules and also some additional transformations preserve contextual equivalence.We also prove a standardisation theorem for fair normal order reduction. The structure of the ordering <=c a is also analysed: Ω is not a least element, and <=c already implies contextual equivalence w.r.t. may-convergence.
We develop a proof method to show that in a (deterministic) lambda calculus with letrec and equipped with contextual equivalence the call-by-name and the call-by-need evaluation are equivalent, and also that the unrestricted copy-operation is correct. Given a let-binding x = t, the copy-operation replaces an occurrence of the variable x by the expression t, regardless of the form of t. This gives an answer to unresolved problems in several papers, it adds a strong method to the tool set for reasoning about contextual equivalence in higher-order calculi with letrec, and it enables a class of transformations that can be used as optimizations. The method can be used in different kind of lambda calculi with cyclic sharing. Probably it can also be used in non-deterministic lambda calculi if the variable x is “deterministic”, i.e., has no interference with non-deterministic executions. The main technical idea is to use a restricted variant of the infinitary lambda-calculus, whose objects are the expressions that are unrolled w.r.t. let, to define the infinite developments as a reduction calculus on the infinite trees and showing a standardization theorem.
The goal of this report is to prove correctness of a considerable subset of transformations w.r.t. contextual equivalence in an extended lambda-calculus LS with case, constructors, seq, let, and choice, with a simple set of reduction rules; and to argue that an approximation calculus LA is equivalent to LS w.r.t. the contextual preorder, which enables the proof tool of simulation. Unfortunately, a direct proof appears to be impossible.
The correctness proof is by defining another calculus L comprising the complex variants of copy, case-reduction and seq-reductions that use variable-binding chains. This complex calculus has well-behaved diagrams and allows a proof of correctness of transformations, and that the simple calculus LS, the calculus L, and the calculus LA all have an equivalent contextual preorder.
The goal of this report is to prove correctness of a considerable subset of transformations w.r.t. contextual equivalence in an extended lambda-calculus LS with case, constructors, seq, let, and choice, with a simple set of reduction rules; and to argue that an approximation calculus LA is equivalent to LS w.r.t. the contextual preorder, which enables the proof tool of simulation. Unfortunately, a direct proof appears to be impossible.
The correctness proof is by defining another calculus L comprising the complex variants of copy, case-reduction and seq-reductions that use variable-binding chains. This complex calculus has well-behaved diagrams and allows a proof of correctness of transformations, and that the simple calculus LS, the calculus L, and the calculus LA all have an equivalent contextual preorder.
The calculus CHF models Concurrent Haskell extended by concurrent, implicit futures. It is a process calculus with concurrent threads, monadic concurrent evaluation, and includes a pure functional lambda-calculus which comprises data constructors, case-expressions, letrec-expressions, and Haskell’s seq. Futures can be implemented in Concurrent Haskell using the primitive unsafeInterleaveIO, which is available in most implementations of Haskell. Our main result is conservativity of CHF, that is, all equivalences of pure functional expressions are also valid in CHF. This implies that compiler optimizations and transformations from pure Haskell remain valid in Concurrent Haskell even if it is extended by futures. We also show that this is no longer valid if Concurrent Haskell is extended by the arbitrary use of unsafeInterleaveIO.
This paper shows equivalence of applicative similarity and contextual approximation, and hence also of bisimilarity and contextual equivalence, in LR, the deterministic call-by-need lambda calculus with letrec extended by data constructors, case-expressions and Haskell's seqoperator. LR models an untyped version of the core language of Haskell. Bisimilarity simplifies equivalence proofs in the calculus and opens a way for more convenient correctness proofs for program transformations.
The proof is by a fully abstract and surjective transfer of the contextual approximation into a call-by-name calculus, which is an extension of Abramsky's lazy lambda calculus. In the latter calculus equivalence of similarity and contextual approximation can be shown by Howe's method. Using an equivalent but inductive definition of behavioral preorder we then transfer similarity back to the calculus LR.
The translation from the call-by-need letrec calculus into the extended call-by-name lambda calculus is the composition of two translations. The first translation replaces the call-by-need strategy by a call-by-name strategy and its correctness is shown by exploiting infinite tress, which emerge by unfolding the letrec expressions. The second translation encodes letrec-expressions by using multi-fixpoint combinators and its correctness is shown syntactically by comparing reductions of both calculi. A further result of this paper is an isomorphism between the mentioned calculi, and also with a call-by-need letrec calculus with a less complex definition of reduction than LR.
Motivated by the question whether sound and expressive applicative similarities for program calculi with should-convergence exist, this paper investigates expressive applicative similarities for the untyped call-by-value lambda-calculus extended with McCarthy's ambiguous choice operator amb. Soundness of the applicative similarities w.r.t. contextual equivalence based on may-and should-convergence is proved by adapting Howe's method to should-convergence. As usual for nondeterministic calculi, similarity is not complete w.r.t. contextual equivalence which requires a rather complex counter example as a witness. Also the call-by-value lambda-calculus with the weaker nondeterministic construct erratic choice is analyzed and sound applicative similarities are provided. This justifies the expectation that also for more expressive and call-by-need higher-order calculi there are sound and powerful similarities for should-convergence.
The pi-calculus is a well-analyzed model for mobile processes and mobile computations.
While a lot of other process and lambda calculi that are core languages of higher-order concurrent and/or functional programming languages use a contextual semantics observing the termination behavior of programs in all program contexts, traditional program equivalences in the pi-calculus are bisimulations and barbed testing equivalences, which observe the communication capabilities of processes under reduction and in contexts.
There is a distance between these two approaches to program equivalence which makes it hard to compare the pi-calculus with other languages. In this paper we contribute to bridging this gap by investigating a contextual semantics of the synchronous pi-calculus with replication and without sums.
To transfer contextual equivalence to the pi-calculus we add a process Stop as constant which indicates success and is used as the base to define and analyze the contextual equivalence which observes may- and should-convergence of processes.
We show as a main result that contextual equivalence in the pi-calculus with Stop conservatively extends barbed testing equivalence in the (Stop-free) pi-calculus. This implies that results on contextual equivalence can be directly transferred to the (Stop-free) pi-calculus with barbed testing equivalence.
We analyze the contextual ordering, prove some nontrivial process equivalences, and provide proof tools for showing contextual equivalences. Among them are a context lemma, and new notions of sound applicative similarities for may- and should-convergence.
Motivated by our experience in analyzing properties of translations between programming languages with observational semantics, this paper clarifies the notions, the relevant questions, and the methods, constructs a general framework, and provides several tools for proving various correctness properties of translations like adequacy and full abstractness. The presented framework can directly be applied to the observational equivalences derived from the operational semantics of programming calculi, and also to other situations, and thus has a wide range of applications.
Our motivation is the question whether the lazy lambda calculus, a pure lambda calculus with the leftmost outermost rewriting strategy, considered under observational semantics, or extensions thereof, are an adequate model for semantic equivalences in real-world purely functional programming languages, in particular for a pure core language of Haskell. We explore several extensions of the lazy lambda calculus: addition of a seq-operator, addition of data constructors and case-expressions, and their combination, focusing on conservativity of these extensions. In addition to untyped calculi, we study their monomorphically and polymorphically typed versions. For most of the extensions we obtain non-conservativity which we prove by providing counterexamples. However, we prove conservativity of the extension by data constructors and case in the monomorphically typed scenario.
Our motivation is the question whether the lazy lambda calculus, a pure lambda calculus with the leftmost outermost rewriting strategy, considered under observational semantics, or extensions thereof, are an adequate model for semantic equivalences in real-world purely functional programming languages, in particular for a pure core language of Haskell. We explore several extensions of the lazy lambda calculus: addition of a seq-operator, addition of data constructors and case-expressions, and their combination, focusing on conservativity of these extensions. In addition to untyped calculi, we study their monomorphically and polymorphically typed versions. For most of the extensions we obtain non-conservativity which we prove by providing counterexamples. However, we prove conservativity of the extension by data constructors and case in the monomorphically typed scenario.
Diese Diplomarbeit beschäftigt sich mit dem Entwurf und der Implementierung der Auslesefirmware für den GET4 Chip im Rahmen des CBM (Compressed Baryonic Matter) Experiments.
Physikalische Experimente mit Teilchenbeschleunigern, wie das geplante CBM Experiment, erzeugen große Mengen an Sensordaten, die aufbereitet, gespeichert und ausgewertet werden müssen. Der GET4 Chip ist ein möglicher TDC (Time to Digital Converter) Chip mit 4 Kanälen für den TOF (Time of Flight) Detektor des CBM Experiments. Der GET4 Chip erzeugt einen Zeitstempel für die Treffer der TOF RPC (Resistive Plate Chambers) Sensoren.
Die Auslese der GET4 Daten wird von einem ROC (Readout Controller Board) übernommen, das mit einem FPGA (Field Programmable Gate Array) ausgestattet ist. Das ROC Board lässt sich über die ROC Firmware für verschiedene Einsatzzwecke flexibel konfigurieren, so dass damit auch andere Frontend Elektronik, wie z.B. der n-XYTER Chip, ausgelesen werden kann. Während dieser Diplomarbeit wurde das SysCore2 mit einem Virtex-4 FX20 als ROC verwendet. Inzwischen ist das SysCore3 verfügbar, das einen deutlich leistungsfähigeren FPGA besitzt. Die bisher verfügbare Firmware für den GET4 war für den Betrieb im 24 Bit Modus konzipiert.
Der bevorzugte Auslesemodus für den GET4 ist der 32 Bit Modus, da der 24 Bit Modus einige Beschränkungen aufweist und die volle Funktionalität des GET4s nur im 32 Bit Modus zur Verfügung steht. Im Rahmen dieser Diplomarbeit wurde die vorhandene 24 Bit Firmware für den 32 Bit Modus erweitert, so dass der zweite Datenkanal des GET4s, sowie der DDR (Double Data Rate) Modus für die Datenübertragung zur Verfügung steht. Neben der Erhöhung der Datenübertragungsraten stand die mögliche Skalierbarkeit der Firmware für die Auslese möglichst vieler GET4 Chips im Fokus. Dazu musste die Firmware umgestaltet werden, um die begrenzten BRAM Ressourcen des FPGAs nicht unnötig zu belegen.
Eine weitere wichtige Neuerung der 32 Bit Firmware ist die automatische Synchronisation der Epochen zwischen ROC und GET4. Dazu werden die Epochennachrichten der GET4s mit der Epoche des ROCs verglichen und bei Bedarf Synchronisationsnachrichten mit der korrekten Epoche an die GET4s gesendet.
Visualisierung von E-Mail-Traffic mit Schwerpunkt auf eine inhaltliche Analyse von Wortmustern
(2010)
E-Mail hat sich zu einem sehr wichtigen Kommunikationsmittel entwickelt, leidet aber aktuell unter einer massiven Verbreitung unerwünschter und unverlangter Inhalte. Diese können für einen Anwender nicht nur lästig sein, sondern auch die vorhandene Netz- und Speicher-Infrastruktur enorm belasten.
Die Notwendigkeit einer Filterung des E-Mail-Traffic hat zu einer Reihe recht unterschiedlicher Methoden geführt, die computergesteuert eine E-Mail auf ihren Spam-Gehalt untersuchen.
Die Motivation hinter dieser Arbeit ist zu prüfen, ob die besonderen Eigenschaften der visuellen Wahrnehmung eines Menschen als unterstützendes Mittel eingesetzt werden können, um E-Mail-Inhalte zu überprüfen und eventuell vorhandene Wort-Muster, die auf Spam deuten, sichtbar zu machen.
Um dieses Ziel zu erreichen musste zuerst eine geeignete Auswahl spamspezifischer Merkmale getroffen werden. Danach wurden Methoden des Text Minings angewendet, um aus dem Inhalt einer E-Mail strukturierte Daten zu gewinnen, die sich zur Repräsentation einer Nachricht eignen und als Grundlage für eine Visualisierung herangezogen werden können. Basierend auf den vorab ausgewählten Spam-Charakteristika wurdenWorteigenschaften mit Hilfe extern angebundener Wortlisten, regulärer Ausdrücke und unter Einsatz eines Wörterbuches überprüft, und die erhaltenen Ergebnisse flossen neben einer einfachen Gewichtung von Worthäufigkeiten in Form einer anwendungsspezifischen Gewichtung mit ein.
Es wurden anschließend zwei verschiedene Sichten konzipiert, um einem Anwender einen Einblick in die extrahierten Daten zu ermöglichen. Es hat sich herausgestellt, dass besonders Treemaps geeignet sind um die anfallenden Datenmengen kompakt abzubilden, aber gleichzeitig einen notwendigen Detailgrad auf einzelne Worteigenschaften gewährleisten.
Das Konzept wurde prototypisch unter Verwendung des Mailservers Mercury/32 sowie einer MySQL-Datenbank implementiert und konnte teilweise aufzeigen, dass es anhand der von der Engine generierten Strukturen möglich ist, spamspezifische Merkmale einer E-Mail unter Verwendung der gewählten Visualisierungstechniken auf eine Weise sichtbar zu machen, die einem Anwender eine Mustererkennung erlauben.
Die Diplomarbeit wurde als Gemeinschaftsarbeit angefertigt und konnte sinnvoll in zwei Bereiche aufgeteilt werden: Die Engine und die Visualisierung. Die konzeptuellen Überlegungen für das Thema sind größtenteils gemeinsam erfolgt, jedoch liegt der Schwerpunkt von Pouneh Khayat Pour im Bereich der Analyse und der von Yvonne Neidert in der Visualisierung.
The human brain is an unparalleled system: Through millions of years of evolution and during a lifespan of learning, our brains have developed remarkable abilities for dealing with incoming sensory data, extracting structure and useful information, and finally drawing the conclusions that result in the actions we take. Understanding the principles behind this machinery and building artificial systems that mimic at least some of these capabilities is a long standing goal in both the scientific and the engineering communities. While this goal still seems unreachable, we have seen tremendous progress when it comes to training data-driven algorithms on vast amounts of training data, e.g. to learn an optimal data model and its parameters in order to accomplish some task. Such algorithms are now omnipresent: they are part of recommender systems, they perform speech recognition and generally build the foundation for many semi-autonomous systems. They start to be integral part of many technical systems modern technical societies rely on for their everyday functioning. Many of these algorithms were originally inspired by biological systems or act as models for sensory data processing in mammalian brains. The response properties of a certain population of neurons in the first stages of the mammalian visual pathway, for example, can be modeled by algorithms such as Sparse Coding (SC), Independent Component Analysis (ICA) or Factor Analysis (FA). These well established learning algorithms typically assume linear interactions between the variables of the model. Most often these relationships are expressed in the form of a matrix-vector products between a matrix with learned dictionary-elements (basis vectors as column vectors) and the latent variables of these models. While on the one hand this linear interaction can sometimes be justified by the physical process for which the machine learning model is proposed, it is on the other hand often chosen just because of its mathematical and practical convenience. From an optimal coding point of view though, one would generally expect that the ideal model closely reflect the core interactions of the system it is modeling. In vision for example, one of the dominant processes giving rise to our sensory percepts are occlusions. Occluding objects are omnipresent in visual scenes and it would not be surprising if the mammalian visual system would be optimized to process occluding structures in the visual data stream. Yet, the established mathematical models of the first stages of the visual processing path (like, e.g., SC, ICA or FA) all assume linear interactions between the active image components. In this thesis we will discuss new models that aim to approximate the effects of occluding components by assuming nonlinear interactions between their activated dictionary elements. We will present learning algorithms that infer optimal parameters for these models given data. In the experiments, we will validate the algorithms on artificial ground truth data and demonstrate their ability to recover the correct model parameters. We will show that the predictions made by these nonlinear models correspond better to the experimental data measured in-vivo than the predictions made by the established linear models. Furthermore, we systematically explore and compare a large space of plausible combinations of hyperparameters and preprocessing schemes in order to eliminate any effects of artefacts on the observed results. Training nonlinear sparse coding models is computationally more demanding than training linear models. In order to perform the numerical experiments described in this thesis we developed a software framework that facilitates the implementation of massive parallel expectation maximization (EM) based learning algorithms. This infrastructure was used for all experiments described in here, as well as by collaborators in projects we will not discuss. Some of the experiments required more than 1017 floating point operations and were run on a computer cluster running on up to 5000 CPU Cores in parallel. Our parallel framework enabled these experiments to be performed.
Frankfurt, an einem gewöhnlichen Morgen gegen 8:00 Uhr: Von Osten strömen zahlreiche Pendler über die A 66 in Richtung Innenstadt. Spätestens »Am Erlenbruch« kommt es zu Staus und zäh fließendem Verkehr. Frankfurter Informatiker können diese Staus mithilfe eines Simulationssystems vorhersagen. Mehr noch: Sie berechnen den Ausstoß von Schadstoffen und deren Verteilung über das Stadtgebiet. Ziel ist die Optimierung von Verkehrsleitstrategien.
Aging of biological systems is controlled by various processes which have a potential impact on gene expression. Here we report a genome-wide transcriptome analysis of the fungal aging model Podospora anserina. Total RNA of three individuals of defined age were pooled and analyzed by SuperSAGE (serial analysis of gene expression). A bioinformatics analysis identified different molecular pathways to be affected during aging. While the abundance of transcripts linked to ribosomes and to the proteasome quality control system were found to decrease during aging, those associated with autophagy increase, suggesting that autophagy may act as a compensatory quality control pathway. Transcript profiles associated with the energy metabolism including mitochondrial functions were identified to fluctuate during aging. Comparison of wild-type transcripts, which are continuously down-regulated during aging, with those down-regulated in the long-lived, copper-uptake mutant grisea, validated the relevance of age-related changes in cellular copper metabolism. Overall, we (i) present a unique age-related data set of a longitudinal study of the experimental aging model P. anserina which represents a reference resource for future investigations in a variety of organisms, (ii) suggest autophagy to be a key quality control pathway that becomes active once other pathways fail, and (iii) present testable predictions for subsequent experimental investigations.
Time-critical applications process a continuous stream of input data and have to meet specific timing constraints. A common approach to ensure that such an application satisfies its constraints is over-provisioning: The application is deployed in a dedicated cluster environment with enough processing power to achieve the target performance for every specified data input rate. This approach comes with a drawback: At times of decreased data input rates, the cluster resources are not fully utilized. A typical use case is the HLT-Chain application that processes physics data at runtime of the ALICE experiment at CERN. From a perspective of cost and efficiency it is desirable to exploit temporarily unused cluster resources. Existing approaches aim for that goal by running additional applications. These approaches, however, a) lack in flexibility to dynamically grant the time-critical application the resources it needs, b) are insufficient for isolating the time-critical application from harmful side-effects introduced by additional applications or c) are not general because application-specific interfaces are used. In this thesis, a software framework is presented that allows to exploit unused resources in a dedicated cluster without harming a time-critical application. Additional applications are hosted in Virtual Machines (VMs) and unused cluster resources are allocated to these VMs at runtime. In order to avoid resource bottlenecks, the resource usage of VMs is dynamically modified according to the needs of the time-critical application. For this purpose, a number of previously not combined methods is used. On a global level, appropriate VM manipulations like hot migration, suspend/resume and start/stop are determined by an informed search heuristic and applied at runtime. Locally on cluster nodes, a feedback-controlled adaption of VM resource usage is carried out in a decentralized manner. The employment of this framework allows to increase a cluster’s usage by running additional applications, while at the same time preventing negative impact towards a time-critical application. This capability of the framework is shown for the HLT-Chain application: In an empirical evaluation the cluster CPU usage is increased from 49% to 79%, additional results are computed and no negative effect towards the HLT-Chain application are observed.
G-CSC Report 2010
(2011)
The present report gives a short summary of the research of the Goethe Center for Scientific Computing (G-CSC) of the Goethe University Frankfurt. G-CSC aims at developing and applying methods and tools for modelling and numerical simulation of problems from empirical science and technology. In particular, fast solvers for partial differential equations (i.e. pde) such as robust, parallel, and adaptive multigrid methods and numerical methods for stochastic differential equations are developed. These methods are highly adanvced and allow to solve complex problems..
The G-CSC is organised in departments and interdisciplinary research groups. Departments are localised directly at the G-CSC, while the task of interdisciplinary research groups is to bridge disciplines and to bring scientists form different departments together. Currently, G-CSC consists of the department Simulation and Modelling and the interdisciplinary research group Computational Finance.
The economic success of the World Wide Web makes it a highly competitive environment for web businesses. For this reason, it is crucial for web business owners to learn what their customers want. This thesis provides a conceptual framework and an implementation of a system that helps to better understand the behavior and potential interests of web site visitors by accounting for both explicit and implicit feedback. This thesis is divided into two parts.
The first part is rooted in computer science and information systems and uses graph theory and an extended click-stream analysis to define a framework and a system tool that is useful for analyzing web user behavior by calculating the interests of the users.
The second part is rooted in behavioral economics, mathematics, and psychology and is investigating influencing factors on different types of web user choices. In detail, a model for the cognitive process of rating products on the Web is defined and an importance hierarchy of the influencing factors is discovered.
Both parts make use of techniques from a variety of research fields and, therefore, contribute to the area of Web Science.
Driven by rapid technological advancements, the amount of data that is created, captured, communicated, and stored worldwide has grown exponentially over the past decades. Along with this development it has become critical for many disciplines of science and business to being able to gather and analyze large amounts of data. The sheer volume of the data often exceeds the capabilities of classical storage systems, with the result that current large-scale storage systems are highly distributed and are comprised of a high number of individual storage components. As with any other electronic device, the reliability of storage hardware is governed by certain probability distributions, which in turn are influenced by the physical processes utilized to store the information. The traditional way to deal with the inherent unreliability of combined storage systems is to replicate the data several times. Another popular approach to achieve failure tolerance is to calculate the block-wise parity in one or more dimensions. With better understanding of the different failure modes of storage components, it has become evident that sophisticated high-level error detection and correction techniques are indispensable for the ever-growing distributed systems. The utilization of powerful cyclic error-correcting codes, however, comes with a high computational penalty, since the required operations over finite fields do not map very well onto current commodity processors. This thesis introduces a versatile coding scheme with fully adjustable fault-tolerance that is tailored specifically to modern processor architectures. To reduce stress on the memory subsystem the conventional table-based algorithm for multiplication over finite fields has been replaced with a polynomial version. This arithmetically intense algorithm is better suited to the wide SIMD units of the currently available general purpose processors, but also displays significant benefits when used with modern many-core accelerator devices (for instance the popular general purpose graphics processing units). A CPU implementation using SSE and a GPU version using CUDA are presented. The performance of the multiplication depends on the distribution of the polynomial coefficients in the finite field elements. This property has been used to create suitable matrices that generate a linear systematic erasure-correcting code which shows a significantly increased multiplication performance for the relevant matrix elements. Several approaches to obtain the optimized generator matrices are elaborated and their implications are discussed. A Monte-Carlo-based construction method allows it to influence the specific shape of the generator matrices and thus to adapt them to special storage and archiving workloads. Extensive benchmarks on CPU and GPU demonstrate the superior performance and the future application scenarios of this novel erasure-resilient coding scheme.
Paging is one of the most prominent problems in the field of online algorithms. We have to serve a sequence of page requests using a cache that can hold up to k pages. If the currently requested page is in cache we have a cache hit, otherwise we say that a cache miss occurs, and the requested page needs to be loaded into the cache. The goal is to minimize the number of cache misses by providing a good page-replacement strategy. This problem is part of memory-management when data is stored in a two-level memory hierarchy, more precisely a small and fast memory (cache) and a slow but large memory (disk). The most important application area is the virtual memory management of operating systems. Accessed pages are either already in the RAM or need to be loaded from the hard disk into the RAM using expensive I/O. The time needed to access the RAM is insignificant compared to an I/O operation which takes several milliseconds.
The traditional evaluation framework for online algorithms is competitive analysis where the online algorithm is compared to the optimal offline solution. A shortcoming of competitive analysis consists of its too pessimistic worst-case guarantees. For example LRU has a theoretical competitive ratio of k but in practice this ratio rarely exceeds the value 4.
Reducing the gap between theory and practice has been a hot research issue during the last years. More recent evaluation models have been used to prove that LRU is an optimal online algorithm or part of a class of optimal algorithms respectively, which was motivated by the assumption that LRU is one of the best algorithms in practice. Most of the newer models make LRU-friendly assumptions regarding the input, thus not leaving much room for new algorithms.
Only few works in the field of online paging have introduced new algorithms which can compete with LRU as regards the small number of cache misses.
In the first part of this thesis we study strongly competitive randomized paging algorithms, i.e. algorithms with optimal competitive guarantees. Although the tight bound for the competitive ratio has been known for decades, current algorithms matching this bound are complex and have high running times and memory requirements. We propose the algorithm OnlineMin which processes a page request in O(log k/log log k) time in the worst case. The best previously known solution requires O(k^2) time.
Usually the memory requirement of a paging algorithm is measured by the maximum number of pages that the algorithm keeps track of. Any algorithm stores information about the k pages in the cache. In addition it can also store information about pages not in cache, denoted bookmarks. We answer the open question of Bein et al. '07 whether strongly competitive randomized paging algorithms using only o(k) bookmarks exist or not. To do so we modify the Partition algorithm of McGeoch and Sleator '85 which has an unbounded bookmark complexity, and obtain Partition2 which uses O(k/log k) bookmarks.
In the second part we extract ideas from theoretical analysis of randomized paging algorithms in order to design deterministic algorithms that perform well in practice. We refine competitive analysis by introducing the attack rate
parameter r, which ranges between 1 and k. We show that r is a tight bound on the competitive ratio of deterministic algorithms.
We give empirical evidence that r is usually much smaller than k and thus r-competitive algorithms have a reasonable performance on real-world traces. By introducing the r-competitive priority-based algorithm class OnOPT we obtain a collection of promising algorithms to beat the LRU-standard. We single out the new algorithm RDM and show that it outperforms LRU and some of its variants on a wide range of real-world traces.
Since RDM is more complex than LRU one may think at first sight that the gain in terms of lowering the number of cache misses is ruined by high runtime for processing pages. We engineer a fast implementation of RDM, and compare it
to LRU and the very fast FIFO algorithm in an overall evaluation scheme, where we measure the runtime of the algorithms and add penalties for each cache miss.
Experimental results show that for realistic penalties RDM still outperforms these two algorithms even if we grant the competitors an idealistic runtime of 0.
An der Universität Frankfurt entwickelte Online-Self-Assessment-Verfahren für die Studiengänge Psychologie und Informatik sollen Studieninteressierten noch vor Studienbeginn auf der Basis von Selbsterkundungsmaßnahmen und Tests eine Rückmeldung über ihre eigenen Fähigkeiten, Motive, personalen Kompetenzen und Interessen mit Blick auf den jeweiligen Studiengang geben. Sowohl die Befunde zur psychometrischen Güte der Verfahren als auch jene zur prognostischen Validität lassen ihren Einsatz zur Feststellung studienrelevanter Kompetenzen als geeignet erscheinen. Da die erfassten Kompetenzen und Merkmale substanzielle Beziehun-gen zu Studienleistungen aufweisen, könnten die Informationen über individuelle Stärken zur Wahl eines geeigneten Studienganges genutzt werden; Schwächen hingegen könnten frühzeitig Hinweise für geeignete Fördermaßnahmen liefern.
We introduce tree-width for first order formulae φ, fotw(φ). We show that computing fotw is fixed-parameter tractable with parameter fotw. Moreover, we show that on classes of formulae of bounded fotw, model checking is fixed parameter tractable, with parameter the length of the formula. This is done by translating a formula φ with fotw(φ)<k into a formula of the k-variable fragment Lk of first order logic. For fixed k, the question whether a given first order formula is equivalent to an Lk formula is undecidable. In contrast, the classes of first order formulae with bounded fotw are fragments of first order logic for which the equivalence is decidable. Our notion of tree-width generalises tree-width of conjunctive queries to arbitrary formulae of first order logic by taking into account the quantifier interaction in a formula. Moreover, it is more powerful than the notion of elimination-width of quantified constraint formulae, defined by Chen and Dalmau (CSL 2005): for quantified constraint formulae, both bounded elimination-width and bounded fotw allow for model checking in polynomial time. We prove that fotw of a quantified constraint formula φ is bounded by the elimination-width of φ, and we exhibit a class of quantified constraint formulae with bounded fotw, that has unbounded elimination-width. A similar comparison holds for strict tree-width of non-recursive stratified datalog as defined by Flum, Frick, and Grohe (JACM 49, 2002). Finally, we show that fotw has a characterization in terms of a cops and robbers game without monotonicity cost.
Poster presentation: Twenty Second Annual Computational Neuroscience Meeting: CNS*2013. Paris, France. 13-18 July 2013.
The synaptic cleft is an extracellular domain that is capable of relaying a presynaptically received electrical signal by diffusive neurotransmitters to the postsynaptic membrane. The cleft is trans-synaptically bridged by ring-like shaped clusters of pre- and postsynaptically localized calcium-dependent adhesion proteins of the N-Cadherin type and is possibly the smallest intercircuit in nervous systems [1]. The strength of association between the pre- and postsynaptic membranes can account for synaptic plasticity such as long-term potentiation [2]. Through neuronal activity the intra- and extracellular calcium levels are modulated through calcium exchangers embedded in the pre- and postsynaptic membrane. Variations of the concentration of cleft calcium induces changes in the N-Cadherin-zipper, that in synaptic resting states is rigid and tightly connects the pre- and postsynaptic domain. During synaptic activity calcium concentrations are hypothesized to drop below critical thresholds which leads to loosening of the N-Cadherin connections and subsequently "unzips" the Cadherin-mediated connection. These processes may result in changes in synaptic strength [2]. In order to investigate the calcium-mediated N-Cadherin dynamics at the synaptic cleft, we developed a three-dimensional model including the cleft morphology and all prominent calcium exchangers and corresponding density distributions [3-6]. The necessity for a fully three-dimensional model becomes apparent, when investigating the effects of the spatial architecture of the synapse [7], [8]. Our data show, that the localization of calcium channels with respect to the N-Cadherin ring has substantial effects on the time-scales on which the Cadherin-zipper switches between states, ranging from seconds to minutes. This will have significant effects on synaptic signaling. Furthermore we see, that high-frequency action potential firing can only be relayed to the Calcium/N-Cadherin-system at a synapse under precise spatial synaptic reorganization.
To truly appreciate the myriad of events which relate synaptic function and vesicle dynamics, simulations should be done in a spatially realistic environment. This holds true in particular in order to explain as well the rather astonishing motor patterns which we observed within in vivo recordings which underlie peristaltic contractionsas well as the shape of the EPSPs at different forms of long-term stimulation, presented both here, at a well characterized synapse, the neuromuscular junction (NMJ) of the Drosophila larva (c.f. Figure 1). To this end, we have employed a reductionist approach and generated three dimensional models of single presynaptic boutons at the Drosophila larval NMJ. Vesicle dynamics are described by diffusion-like partial differential equations which are solved numerically on unstructured grids using the uG platform. In our model we varied parameters such as bouton-size, vesicle output probability (Po), stimulation frequency and number of synapses, to observe how altering these parameters effected bouton function. Hence we demonstrate that the morphologic and physiologic specialization maybe a convergent evolutionary adaptation to regulate the trade off between sustained, low output, and short term, high output, synaptic signals. There seems to be a biologically meaningful explanation for the co-existence of the two different bouton types as previously observed at the NMJ (characterized especially by the relation between size and Po), the assigning of two different tasks with respect to short- and long-time behaviour could allow for an optimized interplay of different synapse types. We can present astonishing similar results of experimental and simulation data which could be gained in particular without any data fitting, however based only on biophysical values which could be taken from different experimental results. As a side product, we demonstrate how advanced methods from numerical mathematics could help in future to resolve also other difficult experimental neurobiological issues.
Functional modules of metabolic networks are essential for understanding the metabolism of an organism as a whole. With the vast amount of experimental data and the construction of complex and large-scale, often genome-wide, models, the computer-aided identification of functional modules becomes more and more important. Since steady states play a key role in biology, many methods have been developed in that context, for example, elementary flux modes, extreme pathways, transition invariants and place invariants. Metabolic networks can be studied also from the point of view of graph theory, and algorithms for graph decomposition have been applied for the identification of functional modules. A prominent and currently intensively discussed field of methods in graph theory addresses the Q-modularity. In this paper, we recall known concepts of module detection based on the steady-state assumption, focusing on transition-invariants (elementary modes) and their computation as minimal solutions of systems of Diophantine equations. We present the Fourier-Motzkin algorithm in detail. Afterwards, we introduce the Q-modularity as an example for a useful non-steady-state method and its application to metabolic networks. To illustrate and discuss the concepts of invariants and Q-modularity, we apply a part of the central carbon metabolism in potato tubers (Solanum tuberosum) as running example. The intention of the paper is to give a compact presentation of known steady-state concepts from a graph-theoretical viewpoint in the context of network decomposition and reduction and to introduce the application of Q-modularity to metabolic Petri net models.
Finding motifs in biological, social, technological, and other types of networks has become a widespread method to gain more knowledge about these networks’ structure and function. However, this task is very computationally demanding, because it is highly associated with the graph isomorphism which is an NP problem (not known to belong to P or NP-complete subsets yet). Accordingly, this research is endeavoring to decrease the need to call NAUTY isomorphism detection method, which is the most time-consuming step in many existing algorithms. The work provides an extremely fast motif detection algorithm called QuateXelero, which has a Quaternary Tree data structure in the heart. The proposed algorithm is based on the well-known ESU (FANMOD) motif detection algorithm. The results of experiments on some standard model networks approve the overal superiority of the proposed algorithm, namely QuateXelero, compared with two of the fastest existing algorithms, G-Tries and Kavosh. QuateXelero is especially fastest in constructing the central data structure of the algorithm from scratch based on the input network.
Integer point sets minimizing average pairwise L1 distance: What is the optimal shape of a town?
(2010)
An n-town, n[is an element of]N , is a group of n buildings, each occupying a distinct position on a 2-dimensional integer grid. If we measure the distance between two buildings along the axis-parallel street grid, then an n-town has optimal shape if the sum of all pairwise Manhattan distances is minimized. This problem has been studied for cities, i.e., the limiting case of very large n. For cities, it is known that the optimal shape can be described by a differential equation, for which no closed-form solution is known. We show that optimal n-towns can be computed in O(n[superscript 7.5]) time. This is also practically useful, as it allows us to compute optimal solutions up to n=80.
Das Ziel dieser Arbeit ist es, eine authentische Verdeckung eingebetteter virtueller 3D-Objekte in augmentierten Bilderwelten bei einer geringen Anzahl an Fotos innerhalb der Bilderwelt zu erreichen. Für die Verdeckung von realen und virtuellen Anteilen einer Augmented Reality-Szene sind Tiefeninformationen notwendig. Diese stammen üblicherweise aus einer 3D-Rekonstruktion, für deren Erstellung sehr viele Eingangsbilder notwendig sind. Im Gegensatz dazu wurde in dieser Arbeit ein System entwickelt, das eine vollständige 3D-Rekonstruktion umgeht. Dieses beruht auf einem direkten bildbasierten Rendering-Ansatz, welcher auch mit unvollständigen Tiefeninformationen eine hohe Bildqualität in Bezug auf eine authentische Verdeckung erreicht. Daraus erschließen sich neue Anwendungsgebiete, wie z.B. die automatisierte Visualisierung von 3D-Planungsdaten und 3D-Produktpräsentationen in Bildern bzw. Bilderwelten, da in diesen Bereichen oftmals nicht genügend große Bildmengen vorhanden sind. Gerade für diese Anwendungsgebiete sind authentische Verdeckungen für die Nutzerakzeptanz der Augmentierung wichtig. Unter authentischer Verdeckung wird die entsprechend der menschlichen Wahrnehmung visuell korrekte Überlagerung zwischen virtuellen Objekten und einzelnen Bildanteilen eines oder mehrerer Fotos verstanden. Das Ergebnis wird in Form einer Bilderwelt (eine bildbasierte 3D-Welt, die die Fotos entsprechend der Bildinhalte räumlich anordnet) präsentiert, die mit virtuellen Objekten erweitert wurde. Folglich ordnet sich diese Arbeit in das Fachgebiet der Augmented Reality ein. Im Rahmen dieser Arbeit wurde ein Verfahren für die bildbasierte Darstellung mit authentischen Verdeckungen auf der Basis von unvollständigen Tiefeninformationen sowie unterschiedliche Verfahren für die notwendige Berechnung der Tiefeninformationen entwickelt und gegenübergestellt. Das Sliced-Image-Rendering-Verfahren rendert mithilfe unvollständiger Tiefeninformationen ein Bild ohne 3D-Geometrie als dreidimensionale Darstellung und realisiert auf diese Weise eine authentische Verdeckung. Das Berechnen der dafür notwendigen Tiefeninformationen eines 2D-Bildes stellt eine gesonderte Herausforderung dar, da die Bilderwelt nur wenige und unvollständige 3D-Informationen der abgebildeten Szene bereitstellt. Folglich kann eine qualitativ hochwertige 3D-Rekonstruktion nicht durchgeführt werden. Die Fragestellung ist daher, wie einzelne Tiefeninformationen berechnet und diese anschließend größeren Bildbereichen zugeordnet werden können. Für diese Tiefenzuordnung wurden im Rahmen der vorliegenden Arbeit drei verschiedene Verfahren konzipiert, die sich in Bezug auf genutzte Daten und deren Verarbeitung unterscheiden. Das Segment-Depth-Matching-Verfahren ordnet Segmenten eines Bildes mithilfe der 3D-Szeneninformationen der Bilderwelt eine Tiefe zu. Hierfür werden Segmentbilder vorausgesetzt. Als Ergebnis liegt für jedes Foto eine Depth-Map vor. Um eine Tiefenzuordnung auch ohne eine vorangehende Segmentierung zu ermöglichen, wurde das Key-Point-Depth-Matching-Verfahren entwickelt. Bei diesem Verfahren werden die 3D-Szeneninformationen der Bilderwelt auf die Bildebene als kreisförmige Sprites projiziert. Die Distanz zur Kamera wird dabei als Tiefenwert für das Sprite verwendet. Alle projizierten Sprites einer Kamera ergeben die Depth-Map. Beide Verfahren liefern Flächen mit Tiefeninformationen, aber keine pixelgenauen Depth-Maps. Um pixelgenaue Depth-Maps zu erzeugen, wurde das Geometry-Depth-Matching-Verfahren entwickelt. Bei diesem Verfahren wird eine Szenengeometrie des abgebildeten Szenenausschnittes erzeugt und dadurch eine pixelgenaue Depth-Map erstellt. Hierfür wird ein semiautomatischer Skizzierungsschritt vorausgesetzt. Die erzeugte Szenengeometrie stellt keine vollständige 3D-Rekonstruktion der Bilderweltenszene dar, da nur ein Szenenausschnitt aus Sicht einer Kamera rekonstruiert wird. Anhand einer technischen Umsetzung erfolgte eine Validierung der konzeptionellen Verfahren. Die daraus resultierenden Ergebnisse wurden anhand verschiedener Bilderweltenszenen mit unterschiedlichen Eigenschaften (Außen- und Innenraumszenen, detailreich und -arm, unterschiedliche Bildmengen) evaluiert. Die Evaluierung des Sliced-Image-Renderings zeigt, dass mithilfe unvollständiger Tiefeninformationen der entwickelten Depth-Matching-Verfahren und unter Einhaltung der gestellten Anforderungen (wenig Eingabefotos, kleine Szenen, keine 3D-Rekonstruktion) eine authentische Verdeckung eingebetteter virtueller 3D-Objekte in Bilderwelten realisiert werden kann. Mithilfe des entwickelten Systems können bildbasierte Anwendungen auch mit kleinen Fotomengen Augmentierungen mit hoher Bildqualität in Bezug auf eine authentische Verdeckung realisieren.
Paging is one of the prominent problems in the field of on-line algorithms. While in the deterministic setting there exist simple and efficient strongly competitive algorithms, in the randomized setting a tradeoff between competitiveness and memory is still not settled. Bein et al. [4] conjectured that there exist strongly competitive randomized paging algorithms, using o(k) bookmarks, i.e. pages not in cache that the algorithm keeps track of. Also in [4] the first algorithm using O(k) bookmarks (2k more precisely), Equitable2, was introduced, proving in the affirmative a conjecture in [7].
We prove tighter bounds for Equitable2, showing that it requires less than k bookmarks, more precisely ≈ 0.62k. We then give a lower bound for Equitable2 showing that it cannot both be strongly competitive and use o(k) bookmarks. Nonetheless, we show that it can trade competitiveness for space. More precisely, if its competitive ratio is allowed to be (Hk + t), then it requires k/(1 + t) bookmarks.
Our main result proves the conjecture that there exist strongly competitive paging algorithms using o(k) bookmarks. We propose an algorithm, denoted Partition2, which is a variant of the Partition algorithm byMcGeoch and Sleator [13]. While classical Partition is unbounded in its space requirements, Partition2 uses θ(k/ log k) bookmarks. Furthermore, we show that this result is asymptotically tight when the forgiveness steps are deterministic.
In der modernen Hochschullehre haben sich eLearning-Elemente als ein Teil des Lehrrepertoires etabliert. Der Einsatz interaktiver webbasierter Selbstlernmodule (Web Based Trainings (WBT)) ist dabei eine Option. Hochschulen und Unternehmen versprechen sich dadurch neue Möglichkeiten des Lehrens und Lernens, um z. B. einen Ausgleich heterogener Vorerfahrungen sowie eine stärkere aktive Beteiligung der Lernenden zu bewirken. Damit die Erstellung und Strukturierung dieser Inhalte mit möglichst geringem Aufwand erfolgen kann, bieten Autorensysteme Unterstützung.
Zu den Grundfunktionen von Autorensystemen gehören unter anderem, das Einbinden gebräuchlicher Medienformate, die einfache Erstellung von Fragen sowie verschiedene Auswertungs- und Feedbackmöglichkeiten. Obwohl Autorensysteme schon vor vielen Jahren ihre erste praktische Anwendung fanden, gibt es nach wie vor Schwachstellen, die sich auf den gesamten Erstellungsprozess wie auch auf einzelne Funktionen beziehen. Im Detail wird bemängelt, dass die Werkzeuge zu komplex und unflexibel sind. Darüber hinaus fehlt häufig eine zufriedenstellende Verknüpfung der vielen Werkzeuge entlang der Prozesskette zu einer Gesamtlösung.
Des Weiteren wird die Konzentration auf die Produktionsphase kritisiert, wodurch andere wichtige Prozesse in den Hintergrund treten bzw. außer Acht gelassen werden.
Im Rahmen der Zusammenarbeit mit einem Automobilhersteller, für den die erste Version des Autorensystems LernBar weiterentwickelt wurde, spielte der Begriff „Lean Production“ inhaltlich in der Umsetzung der WBTs eine wesentliche Rolle. Die Lean Production, die über viele Jahre für die Automobilindustrie entwickelt, verbessert und angepasst wurde, liefert Optimierungsansätze für den Produktionsbereich. Ein wirtschaftlicher Nutzen des Lean-Ansatzes wird auch in anderen Bereichen gesehen wie z. B. in der Softwareentwicklung („Lean Software Development“) oder im Management („Lean Management“). Dabei bietet die Wertschöpfungsorientierung Lösungen für die widersprüchlichen Ziele mehr Leistungen zu geringeren Kosten, schneller und in höherer Qualität zugleich zu liefern. Aus der Grundidee der Lean Production entwickelte sich vorliegendes Dissertationsthema in Bezug darauf, inwiefern sich diese Prinzipien auf den WBT-Produktionsprozess übertragen lassen und die LernBar (das hierfür weiterentwickelnde Autorensystem) dabei Unterstützung bieten kann.
Zunächst wurde analysiert, welche Werkzeuge und Hilfestellungen benötigt werden, um unter dem Aspekt der Lean Production WBTs im universitären Umfeld erstellen zu können. In diesem Zusammenhang wurden Merkmale einer „Lean Media Production“ definiert sowie konzeptionell und technisch umgesetzt. Zur Verbesserung der Prozesse flossen Ergebnisse aus empirischer und praktischer Forschung ein. Im Vergleich zu anderen Entwicklungen bei denen häufig das Hauptziel eine umfangreiche Funktionalität ist, werden u.a. folgende übertragbare Ziele bei der Umsetzung verfolgt: Verschwendung vermeiden, eine starke Einbeziehung der Kunden, Werkzeuge die nahtlos ineinandergreifen, eine hohe Flexibilität und eine stetige Qualitätsverbesserung.
Zur Erreichung dieser Zielsetzungen wurden alle Prozesse kontinuierlich verbessert, sich auf das Wesentliche und die Wertschöpfung konzentriert sowie überflüssige Schritte eliminiert. Demnach ist unter dem Begriff „Lean Media Production“ ein skalierbarer, effizienter und effektiver Produktionsprozess zu verstehen, in dem alle Werkzeuge ineinandergreifen.
Die Realisierung der „Lean Media Production“ erfolgte anhand des Autorensystems LernBar, wobei die typischen Softwareentwicklungsphasen Entwurf, Implementierung und Evaluierung mehrfach durchlaufen wurden. Ausschlaggebend dabei war, dass der „Lean“-Aspekt berücksichtigt wurde und dies somit eine neue Vorgehensweise bei der Umsetzung eines Autorensystems darstellt. Im Verlauf der Entwicklungen ergaben sich, durch eine formative Evaluation, den Einsatz in Projekten und eine empirische Begleitforschung, neue Anforderungen an das System. Ein Vergleich der zwei Produktionssysteme, Automobil vs. WBT-Produktion, zeigt und bestätigt die Erwartung, dass nicht alle Prinzipien der Lean Production übertragbar sind.
Dennoch war diese Untersuchung notwendig, da sie Denkanstöße zur Entwicklung und Optimierung des Erstellungsprozesses eines WBTs gab. Auch die Ergebnisse der abschließenden Online-Befragung ergaben, dass die Ziele der Arbeit erreicht wurden, dass aber weiterer Optimierungsbedarf besteht. Die LernBar Release 3 bietet für alle Produktionsphasen Werkzeuge an, durch die eine effektive und effiziente Erstellung von WBTs von der Idee bis zur Distribution möglich ist.
Stand noch vor fünf Jahren zu Beginn dieser Arbeit das Endprodukt bei der LernBar Entwicklung im Vordergrund, verlagerte sich durch den Einfluss dieser Dissertation der Schwerpunkt auf den gesamten Produktionsprozess. Unter Berücksichtigung der in diesem Zusammenhang entwickelten Prinzipien einer „Lean Media Production“, nehmen bspw. die Wirtschaftlichkeit und die starke Kundenorientierung während des Produktionsprozesses einen wichtigen Stellenwert ein. Dieser Ansatz ist eine neue Vorgehensweise im Bereich der Entwicklung von Autorensystemen, der seine Anerkennung und Professionalität durch die Ergebnisse des selbstentwickelten Evaluationsbogens sowie dem stetig wachsenden Einsatz in Schulen, Hochschulen und Unternehmen belegen kann.
In weiteren Forschungsarbeiten ist zu untersuchen, welche Lean Production Prinzipien zu verwenden oder anzupassen sind, wenn z. B. in größeren Teams oder mobil produziert wird. Des Weiteren sollte überprüft werden, inwieweit die Lernenden mit dem Endprodukt zufrieden sind und in ihrem Lernprozess unterstützt werden. Durch diese Forschungsarbeit wurde ein Beitrag dazu geleistet, die Lehre und Ausbildung zu optimieren, indem die Autoren/Lehrende in der Erstellung ihrer digitalen Lerninhalte im gesamten Prozess von aufeinander abgestimmten Werkzeugen unterstützt werden.